Assessing the Integration of United Nations Sustainable Development Goals in a University General Education Curriculum

Abstract

Higher education plays an essential role in achieving United Nations Sustainable Development Goals (SDGs). However, there are only scattered studies on monitoring how universities holistically promote SDGs through their curriculum. The main purpose of this study is to investigate the connection of existing general education courses in a university to SDG education. In particular, we want to know how can general education courses be classified according to SDGs. In this poster paper, we use machine learning approaches to tag the 167 general education courses in a university with SDGs, then analyze the results based on visualizations. Our training dataset comes from the OSDG public community dataset which had been verified by the community. Meanwhile, the learning outcomes and descriptions of general education courses had been used for the classification. We use the multinomial logistic regression algorithm as the algorithm and for the classification. Examples of calculated SDG probability of courses and the overall curriculum were used for illustrating the functions of the proposed approach.